Portable computing devices, for example Portable Navigation Devices (PNDs) that include GPS (Global Positioning System) signal reception and processing functionality are well known and are widely employed as in-car or other vehicle navigation systems. Examples of known PNDs include the GO IIVE 1005 model manufactured and supplied by TomTom International B.V.
The utility of such PNDs is manifested primarily in their ability to determine a route between a first location (usually a start or current location) and a second location (usually a destination). These locations can be input by a user of the device, by any of a wide variety of different methods, for example by postcode, street name and house number, previously stored “well known” destinations (such as famous locations, municipal locations (such as sports grounds or swimming baths) or other points of interest), and favourite or recently visited destinations.
The PND determines the route based upon stored geographical data, usually in the form of a digital map. The stored geographical data can include data concerning a wide variety of features, for example the position and characteristics of roads or other thoroughfares, the position and characteristics of points of interest, and the position and characteristics of geographical features, for example rivers, coastlines, or mountains.
In operation, most PNDs periodically log their own position as a function of time, for example every five seconds. PNDs can also log other, associated data such as speed or direction of travel as a function of time. The data logged by PNDs or other portable computing devices, can be referred to as probe data. It is known to obtain probe data from a large number of PNDs or other portable computing devices, and to process the probe data in order to verify or supplement existing geographical data, for example existing digital maps.
Roads or other routes can be represented in a digital map by separate segments. The digital map can include speed data that represents the expected speed of travel over each segment of a road or other route. Such speed data is obtained from expected average travel speeds over roads of different types or is obtained from probe data representing actual travel of large numbers of vehicles over each road or other route in the digital map.
The speed data can be used in known systems to determine the fastest route to a particular destination, to plan routes and/or to determine an estimated time of arrival (ETAs) at the destination. An example of a system that uses speed data in such a way is the IQ Routes(RTM) system produced by TomTom International B.V.
Whilst speed data can be used to calculate preferred routes and ETAs, the accuracy of such calculations can be hindered due to the unpredictability of traffic. Speed profiles obtained from probe data usually represent long term averages, averaged over periods longer than many types of traffic fluctuations. Local short-lived events or fluctuations of traffic can invalidate, or render inaccurate, a specific speed profile of a road segment. For example, one such event is bad weather, which can easily double ETAs.
Many weather events are local in nature, and are not represented well by typical weather forecast data, which covers large areas with limited accuracy. Many weather-related events, for example ice formation on particular road portions, or the presence of standing water on a road, are local in nature and may be dependent on local geography and road conditions as well as forecast weather conditions. Furthermore, the precise boundary or duration of an area of precipitation or other weather condition may not be represented accurately by weather forecast data.